Triple
T9878586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amen |
E240142
|
entity |
| Predicate | hasISOLanguageCode |
P13919
|
FINISHED |
| Object | en |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: en | Statement: [Amen, hasISOLanguageCode, en]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISOLanguageCode Context triple: [Amen, hasISOLanguageCode, en]
-
A.
hasISOCode
Indicates that an entity is associated with a specific standardized ISO code that uniquely identifies it according to ISO conventions.
-
B.
hasLinguisticCode
chosen
Indicates that an entity is associated with a specific linguistic identifier or code (such as a language or script code) that characterizes its linguistic properties.
-
C.
hasLanguageIsolate
Indicates that an entity’s language is not demonstrably related to any other known language family, standing as a unique linguistic isolate.
-
D.
hasISO639MacrolanguageCode
Indicates that a language entity is associated with a specific ISO 639 macrolanguage code that represents a broader language grouping.
-
E.
hasISO639_5Code
Indicates that a language or language group is associated with a specific ISO 639-5 code that identifies it within the ISO 639-5 language classification standard.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb4135c108190b3330e929509699d |
completed | April 2, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:37 p.m.